Category Archives: Hockey

My Model Monday: Hockey Aging Curves

In this week’s My Model Monday, I explored aging curves in not just the NHL, but in other professional leagues and junior hockey leagues. First and foremost, what are aging curves? Aging curves are just what they sound like: curves that associate player performance and health over time. For a point of reference, despite his mighty accomplishments at an old age, Jaromir Jagr saw his point production dip from over a point per game at age 25 to about 0.3 PTS/G at age 45. Jaromir Jagr is an incredibly interesting case and likely outlier, as few players have played into their mid-forties. At any rate, one can imagine that many players experience similar increases and decreases in production with age; therefore, using many samples of players, one can construct a curve that resembles a mean of all players aging, or, as we like to say in the reinsurance industry, an industry exposure curve. Continue reading My Model Monday: Hockey Aging Curves

NHL Draft Model Results 2018 (Preliminary)

Below is results to our (preliminary) NHL Draft Model that uses prospects’ statistical production, physical measurements, and other variables to predict the likelihood that a players assume a specific NHL Role (i.e., First Line / Top Pair, Second / Third Line / 2nd pair defensemen, Fourth Line / Bottom pair defensemen, and Non-NHL player). The model is still being fine-tuned, hence the preliminary results, and an in-depth methodology article will come in the future. In addition to the aforementioned role probabilities, there is also a predicted NHL point per game that is derived from our Hockey Translation Factors.

Continue reading NHL Draft Model Results 2018 (Preliminary)

Model 284 Podcast: Hockey Translation Factors and Peter Lindblad Interview

In this episode of the Model 284 podcast, we catch you up on everything going on at Model 284, breakdown our Hockey League Translations Model, and interview professional hockey player Peter Lindblad to discuss analytics in hockey, professional hockey in Europe, Sunday punting, and more.

Hockey League Translation Factors: Methodology

I. Introduction

If you didn’t know, there are a lot of people in the world—7.6 billion to be exact! There are also a lot of people that play hockey. As a result, there are a lot of hockey leagues in the world. Wow. Okay, moving on… The National Hockey League (NHL) is seen as the premier hockey league in the world, but players don’t start their hockey career in the NHL, and most never make it to the NHL. Some would argue that it is possible to have a successful and prosperous hockey career even if you never play in the NHL. In this article, I attempt to quantify the differences between these leagues; more specifically, translating individual player production from one league to the next. This would allow us to say things such as Tony Cameranesi registered 50 points in 50 games, or 1.0 point per game, in the NCAA, thus you would expect him to produce xx amount in the AHL, yy amount in the KHL, zz amount in the NHL, etc.

Continue reading Hockey League Translation Factors: Methodology

2017-18 NHL Playoff Bracket

Below is our Model 284 consensus bracket for the 2017-18 NHL Playoffs as well as some Model Factoids. As you will see from our first round Predictions and playoff simulation results, we do not necessarily pick the model’s predicted winner for every single game, but use all available information (e.g. injuries, areas model might be lacking, etc.) to make the best prediction on each series.

Continue reading 2017-18 NHL Playoff Bracket